Computer Vision

Master data has played a significant role in improving operational efficiencies and has attracted the attention of many large businesses over the decade. Recent professional searches have also proved a significant growth in the practice and research of managing these master data assets.

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  • Artificial Intelligence
  • Last Updated On: 
    Sat, 03/14/2020 - 00:20

    Pressing demand of workload along with social media interaction leads to diminished alertness during work hours. Researchers attempted to measure alertness level from various cues like EEG, EOG, Video-based eye movement analysis, etc. Among these, video-based eyelid and iris motion tracking gained much attention in recent years. However, most of these implementations are tested on video data of subjects without spectacles. These videos do not pose a challenge for eye detection and tracking.

    195 views
  • Computer Vision
  • Last Updated On: 
    Thu, 03/19/2020 - 02:40

    Four fully annotated marine image datasets. The annotations are given as train and test splits that can be used to evaluate machine learning methods.

    63 views
  • Computer Vision
  • Last Updated On: 
    Tue, 03/03/2020 - 04:53

    CUPSNBOTTLES is an object data set, recorded by a mobile service robot. There are 10 object classes, each with a varying number of samples. Additionally, there is a clutter class, containing samples where the object detector failed.

    118 views
  • Computer Vision
  • Last Updated On: 
    Fri, 02/28/2020 - 11:47

    Along with the increasing use of unmanned aerial vehicles (UAVs), large volumes of aerial videos have been produced. It is unrealistic for humans to screen such big data and understand their contents. Hence methodological research on the automatic understanding of UAV videos is of paramount importance.

    182 views
  • Artificial Intelligence
  • Last Updated On: 
    Wed, 07/01/2020 - 20:54

    This is a dataset having paired thermal-visual images collected over 1.5 years from different locations in Chitrakoot, India and Prayagraj, India. The images can be broadly classified into greenery, urban, historical buildings and crowd data.

    The crowd data was collected from the Maha Kumbh Mela 2019, Prayagraj, which is the largest religious fair in the world and is held every 12 years.

    64 views
  • Computer Vision
  • Last Updated On: 
    Wed, 02/26/2020 - 07:37

    As developers create or analyze an application,they often want to visualize the code through some graphical notation that aids their understanding of the code’s structure or behavior. In order to do this, we develop a integrated debugger.The debugger first record the walkthrough of application as assembly instructions by dynamic way.Then compression mapping block transforms previous outcome into three-dimensional-linked list structure,which then transformed into tree structure by the improved suffix tree algorithm.

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  • Computer Vision
  • Last Updated On: 
    Mon, 03/30/2020 - 16:05

    The zizania image dataset consists of a total of 4900 zizanias. The quantity of high quality samples is 2648 and defective quality samples is 2252.

    There are four classes in the apple image dataset, which are apples with a diameter greater than 90 mm, between 80 mm and 90 mm, less than 80 mm, and diseases and insect pests. The quantity distributionin above categories are 3647 (51.19%), 2464 (34.59%), 558 (7.83%), 455 (6.39%).

    95 views
  • Artificial Intelligence
  • Last Updated On: 
    Mon, 02/24/2020 - 00:10

    Beijing Building Dataset(BGB) is an elevation satellite image dataset which is integrated by satellite image and aerial photograph for building detection and identification. It contains 2000 images from Google Earth History Map of five different areas in Beijing on November 24th, 2016, and all these images are 512*512 in resolution ratio with a precision of 0.458m. It covers more than 100 km2 geographic areas of Beijing both in suburbs and urban areas.

    114 views
  • Artificial Intelligence
  • Last Updated On: 
    Mon, 03/09/2020 - 20:30

    In recent years, the utilization of biometric information has become more and more common for various forms of identity verification and user authentication. However, as a consequence of the widespread use and storage of biometric information, concerns regarding sensitive information leakage and the protection of users' privacy have been raised. Recent research efforts targeted these concerns by proposing the Semi-Adversarial Networks (SAN) framework for imparting gender privacy to face images.

    35 views
  • Computer Vision
  • Last Updated On: 
    Fri, 02/14/2020 - 12:22

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